AI and Machine Learning for Healthcare

Artificial intelligence (AI) and machine learning (ML) in healthcare comprise a rapidly expanding and very promising field. The marriage of technology and health has the potential to empower medical professionals and patients alike, while drastically cutting the cost of healthcare. Using a measured no-hype approach, this video will help technology entrepreneurs, product managers, and health care executives understand what can be done with AI and ML in healthcare today and what concepts are most crucial to producing valuable applications in the near future.

• Understand the basics of putting together a health-tech data pipeline from raw datasets
• Learn how pipelines turn unstructured data (e.g., medical records and open ended surveys) into inputs for modeling and metrics
• Explore the unsupervised learning methodologies that search for novel insights in large health datasets
• Understand the forecasting and classification methodologies for individual and population level health
• Get up to date on Assist-AI in health-related user interactions and clinical decision making
• Become aware of the data challenges inherent in many scenarios within healthcare applications

Aileen Nielsen is a software engineer at One Drop, a company working on diabetes-management products. A member of the New York City Bar Association’s Science and Law committee, Aileen holds degrees in anthropology, law, and physics from Princeton, Yale, and Columbia, respectively.